Publications by authors named "Matthew W Fittall"

6 Publications

  • Page 1 of 1

Drivers underpinning the malignant transformation of giant cell tumour of bone.

J Pathol 2020 Dec 6;252(4):433-440. Epub 2020 Oct 6.

Department of Pathology (research), University College London Cancer Institute, London, UK.

The rare benign giant cell tumour of bone (GCTB) is defined by an almost unique mutation in the H3.3 family of histone genes H3-3A or H3-3B; however, the same mutation is occasionally found in primary malignant bone tumours which share many features with the benign variant. Moreover, lung metastases can occur despite the absence of malignant histological features in either the primary or metastatic lesions. Herein we investigated the genetic events of 17 GCTBs including benign and malignant variants and the methylation profiles of 122 bone tumour samples including GCTBs. Benign GCTBs possessed few somatic alterations and no other known drivers besides the H3.3 mutation, whereas all malignant tumours harboured at least one additional driver mutation and exhibited genomic features resembling osteosarcomas, including high mutational burden, additional driver event(s), and a high degree of aneuploidy. The H3.3 mutation was found to predate the development of aneuploidy. In contrast to osteosarcomas, malignant H3.3-mutated tumours were enriched for a variety of alterations involving TERT, other than amplification, suggesting telomere dysfunction in the transformation of benign to malignant GCTB. DNA sequencing of the benign metastasising GCTB revealed no additional driver alterations; polyclonal seeding in the lung was identified, implying that the metastatic lesions represent an embolic event. Unsupervised clustering of DNA methylation profiles revealed that malignant H3.3-mutated tumours are distinct from their benign counterpart, and other bone tumours. Differential methylation analysis identified CCND1, encoding cyclin D1, as a plausible cancer driver gene in these tumours because hypermethylation of the CCND1 promoter was specific for GCTBs. We report here the genomic and methylation patterns underlying the rare clinical phenomena of benign metastasising and malignant transformation of GCTB and show how the combination of genomic and epigenomic findings could potentially distinguish benign from malignant GCTBs, thereby predicting aggressive behaviour in challenging diagnostic cases. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.
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http://dx.doi.org/10.1002/path.5537DOI Listing
December 2020

COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: a prospective cohort study.

Lancet Oncol 2020 10 24;21(10):1309-1316. Epub 2020 Aug 24.

Department of Oncology, University of Oxford, Oxford, UK.

Background: Patients with cancer are purported to have poor COVID-19 outcomes. However, cancer is a heterogeneous group of diseases, encompassing a spectrum of tumour subtypes. The aim of this study was to investigate COVID-19 risk according to tumour subtype and patient demographics in patients with cancer in the UK.

Methods: We compared adult patients with cancer enrolled in the UK Coronavirus Cancer Monitoring Project (UKCCMP) cohort between March 18 and May 8, 2020, with a parallel non-COVID-19 UK cancer control population from the UK Office for National Statistics (2017 data). The primary outcome of the study was the effect of primary tumour subtype, age, and sex and on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prevalence and the case-fatality rate during hospital admission. We analysed the effect of tumour subtype and patient demographics (age and sex) on prevalence and mortality from COVID-19 using univariable and multivariable models.

Findings: 319 (30·6%) of 1044 patients in the UKCCMP cohort died, 295 (92·5%) of whom had a cause of death recorded as due to COVID-19. The all-cause case-fatality rate in patients with cancer after SARS-CoV-2 infection was significantly associated with increasing age, rising from 0·10 in patients aged 40-49 years to 0·48 in those aged 80 years and older. Patients with haematological malignancies (leukaemia, lymphoma, and myeloma) had a more severe COVID-19 trajectory compared with patients with solid organ tumours (odds ratio [OR] 1·57, 95% CI 1·15-2·15; p<0·0043). Compared with the rest of the UKCCMP cohort, patients with leukaemia showed a significantly increased case-fatality rate (2·25, 1·13-4·57; p=0·023). After correction for age and sex, patients with haematological malignancies who had recent chemotherapy had an increased risk of death during COVID-19-associated hospital admission (OR 2·09, 95% CI 1·09-4·08; p=0·028).

Interpretation: Patients with cancer with different tumour types have differing susceptibility to SARS-CoV-2 infection and COVID-19 phenotypes. We generated individualised risk tables for patients with cancer, considering age, sex, and tumour subtype. Our results could be useful to assist physicians in informed risk-benefit discussions to explain COVID-19 risk and enable an evidenced-based approach to national social isolation policies.

Funding: University of Birmingham and University of Oxford.
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http://dx.doi.org/10.1016/S1470-2045(20)30442-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7444972PMC
October 2020

COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study.

Lancet 2020 06 28;395(10241):1919-1926. Epub 2020 May 28.

Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; University Hospitals Birmingham, Birmingham, UK.

Background: Individuals with cancer, particularly those who are receiving systemic anticancer treatments, have been postulated to be at increased risk of mortality from COVID-19. This conjecture has considerable effect on the treatment of patients with cancer and data from large, multicentre studies to support this assumption are scarce because of the contingencies of the pandemic. We aimed to describe the clinical and demographic characteristics and COVID-19 outcomes in patients with cancer.

Methods: In this prospective observational study, all patients with active cancer and presenting to our network of cancer centres were eligible for enrolment into the UK Coronavirus Cancer Monitoring Project (UKCCMP). The UKCCMP is the first COVID-19 clinical registry that enables near real-time reports to frontline doctors about the effects of COVID-19 on patients with cancer. Eligible patients tested positive for severe acute respiratory syndrome coronavirus 2 on RT-PCR assay from a nose or throat swab. We excluded patients with a radiological or clinical diagnosis of COVID-19, without a positive RT-PCR test. The primary endpoint was all-cause mortality, or discharge from hospital, as assessed by the reporting sites during the patient hospital admission.

Findings: From March 18, to April 26, 2020, we analysed 800 patients with a diagnosis of cancer and symptomatic COVID-19. 412 (52%) patients had a mild COVID-19 disease course. 226 (28%) patients died and risk of death was significantly associated with advancing patient age (odds ratio 9·42 [95% CI 6·56-10·02]; p<0·0001), being male (1·67 [1·19-2·34]; p=0·003), and the presence of other comorbidities such as hypertension (1·95 [1·36-2·80]; p<0·001) and cardiovascular disease (2·32 [1·47-3·64]). 281 (35%) patients had received cytotoxic chemotherapy within 4 weeks before testing positive for COVID-19. After adjusting for age, gender, and comorbidities, chemotherapy in the past 4 weeks had no significant effect on mortality from COVID-19 disease, when compared with patients with cancer who had not received recent chemotherapy (1·18 [0·81-1·72]; p=0·380). We found no significant effect on mortality for patients with immunotherapy, hormonal therapy, targeted therapy, radiotherapy use within the past 4 weeks.

Interpretation: Mortality from COVID-19 in cancer patients appears to be principally driven by age, gender, and comorbidities. We are not able to identify evidence that cancer patients on cytotoxic chemotherapy or other anticancer treatment are at an increased risk of mortality from COVID-19 disease compared with those not on active treatment.

Funding: University of Birmingham, University of Oxford.
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http://dx.doi.org/10.1016/S0140-6736(20)31173-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7255715PMC
June 2020

Translating insights into tumor evolution to clinical practice: promises and challenges.

Genome Med 2019 03 29;11(1):20. Epub 2019 Mar 29.

The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UK.

Accelerating technological advances have allowed the widespread genomic profiling of tumors. As yet, however, the vast catalogues of mutations that have been identified have made only a modest impact on clinical medicine. Massively parallel sequencing has informed our understanding of the genetic evolution and heterogeneity of cancers, allowing us to place these mutational catalogues into a meaningful context. Here, we review the methods used to measure tumor evolution and heterogeneity, and the potential and challenges for translating the insights gained to achieve clinical impact for cancer therapy, monitoring, early detection, risk stratification, and prevention. We discuss how tumor evolution can guide cancer therapy by targeting clonal and subclonal mutations both individually and in combination. Circulating tumor DNA and circulating tumor cells can be leveraged for monitoring the efficacy of therapy and for tracking the emergence of resistant subclones. The evolutionary history of tumors can be deduced for late-stage cancers, either directly by sampling precursor lesions or by leveraging computational approaches to infer the timing of driver events. This approach can identify recurrent early driver mutations that represent promising avenues for future early detection strategies. Emerging evidence suggests that mutational processes and complex clonal dynamics are active even in normal development and aging. This will make discriminating developing malignant neoplasms from normal aging cell lineages a challenge. Furthermore, insight into signatures of mutational processes that are active early in tumor evolution may allow the development of cancer-prevention approaches. Research and clinical studies that incorporate an appreciation of the complex evolutionary patterns in tumors will not only produce more meaningful genomic data, but also better exploit the vulnerabilities of cancer, resulting in improved treatment outcomes.
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http://dx.doi.org/10.1186/s13073-019-0632-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6440005PMC
March 2019

Recurrent rearrangements of FOS and FOSB define osteoblastoma.

Nat Commun 2018 06 1;9(1):2150. Epub 2018 Jun 1.

Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, CB10 1SA, UK.

The transcription factor FOS has long been implicated in the pathogenesis of bone tumours, following the discovery that the viral homologue, v-fos, caused osteosarcoma in laboratory mice. However, mutations of FOS have not been found in human bone-forming tumours. Here, we report recurrent rearrangement of FOS and its paralogue, FOSB, in the most common benign tumours of bone, osteoblastoma and osteoid osteoma. Combining whole-genome DNA and RNA sequences, we find rearrangement of FOS in five tumours and of FOSB in one tumour. Extending our findings into a cohort of 55 cases, using FISH and immunohistochemistry, provide evidence of ubiquitous mutation of FOS or FOSB in osteoblastoma and osteoid osteoma. Overall, our findings reveal a human bone tumour defined by mutations of FOS and FOSB.
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http://dx.doi.org/10.1038/s41467-018-04530-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5984627PMC
June 2018

Left ventricular pacing should be considered when biventricular pacing worsens heart failure: left ventricular pacing instead of biventricular pacing?

J Interv Card Electrophysiol 2012 Jan 21;33(1):37-41. Epub 2011 Sep 21.

Department of Cardiovascular Electrophysiology, The Heart Hospital, University College London NHS Trust, 16-18 Westmoreland Street, W1G 8PH, London, UK.

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http://dx.doi.org/10.1007/s10840-011-9617-6DOI Listing
January 2012